MARATTO

article · Kafr El-Sheikh Journal of Information Sciences

The classification of mushroom using ML

20233 citationsOpen accessUniversity of Sadat City

Abstract

The Mushroom is kind of fungi. Major health benefits of mushrooms include their ability to kill cancer cells. The goal of this research is to determine the most effective method for mushroom classification, with the categories of deadly and nonpoisonous mushrooms being used. Separate from plants and animals, they belong in their own realm. In terms of how they get nutrients, fungi are different from plants and mammals. Mushrooms are classified as edible and poisoned. To distinguish between two varieties of mushrooms, we can use machine learning, which is used in classification. There are numerous machine learning algorithms that perform classification, but in our model, I utilize random forest, MLP, Linear Regression and decision tree on the features of the mushroom to categorize it into edible and poisonous. Random Forest achieves high accuracy 98.70%. from these results, we can use Ml to differentiate between two varieties of mushrooms because it is used in classification efficiently.

Research topics

  • Smart Agriculture and AI

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.21608/kjis.2023.221370.1016

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.